This paper analyzes the optimization problem of mutation probability in genetic algorithms by applying the definition of i-bit improved sub-space. Then fuzzy reasoning technique is adopted to determine the optimal mut...This paper analyzes the optimization problem of mutation probability in genetic algorithms by applying the definition of i-bit improved sub-space. Then fuzzy reasoning technique is adopted to determine the optimal mutation probability in different conditions. The superior convergence property of the new method is evaluated by applying it to two simulation examples.展开更多
基金Supported by the Climbing PrOgram-National Key Project for Fundamental Research in China, Grant NSC92097
文摘This paper analyzes the optimization problem of mutation probability in genetic algorithms by applying the definition of i-bit improved sub-space. Then fuzzy reasoning technique is adopted to determine the optimal mutation probability in different conditions. The superior convergence property of the new method is evaluated by applying it to two simulation examples.